Background: Many states and localities throughout the U.S. have adopted higher minimum wages. Higher labor costs among low-wage food system workers could result in higher food prices. Methods: Using a market basket of 106 foods, food prices were collected at affected chain supermarket stores in Seattle and same-chain unaffected stores in King County (n = 12 total, six per location). Prices were collected at 1 month pre- (March 2015) and 1-month post-policy enactment (May 2015), then again 1-year post-policy enactment (May 2016). Unpaired t-tests were used to detect price differences by location at fixed time while paired t-tests were used to detect price difference across time with fixed store chain. A multi-level, linear differences-in-differences model, was used to detect the changes in the average market basket item food prices over time across regions, overall and by food group. Results: There were no significant differences in overall market basket or item-level costs at one-month (-$0.01, SE = 0.05, p = 0.884) or one-year post-policy enactment (-$0.02, SE = 0.08, p = 0.772). No significant increases were observed by food group. Conclusions: There is no evidence of change in supermarket food prices by market basket or increase in prices by food group in response to the implementation of Seattles minimum wage ordinance.

Abstract Background Little research has explored who responds better to an automated vs. human advisor for health behaviors in general, and for physical activity (PA) promotion in particular. The purpose of this study was to explore baseline factors (i.e., demographics, motivation, interpersonal style, and external resources) that moderate intervention efficacy delivered by either a human or automated advisor. Methods Data were from the CHAT Trial, a 12-month randomized controlled trial to increase PA among underactive older adults (full trial N = 218) via a human advisor or automated interactive voice response advisor. Trial results indicated significant increases in PA in both interventions by 12 months that were maintained at 18-months. Regression was used to explore moderation of the two interventions. Results Results indicated amotivation (i.e., lack of intent in PA) moderated 12-month PA (d = 0.55, p < 0.01) and private self-consciousness (i.e., tendency to attune to one’s own inner thoughts and emotions) moderated 18-month PA (d = 0.34, p < 0.05) but a variety of other factors (e.g., demographics) did not (p > 0.12). Conclusions Results provide preliminary evidence for generating hypotheses about pathways for supporting later clinical decision-making with regard to the use of either human- vs. computer-delivered interventions for PA promotion.